Using Machine Learning and Data Science to Solve Real Business Problems (DataEDGE 2018)
Sourav Dey, Managing Director of Machine Learning, Manifold — AI and machine learning have the power to transform entire industries. Companies in consumer facing industries like banking, healthcare, and e-commerce that aren’t using these new tools and advances today run the real risk of failure as we gear towards an automated future.
Sourav Dey, Managing Director and Head of Data Science at Manifold, will talk about the importance for today’s companies to adopt ML and data science and how they can do it. Using specific real world use cases, Sourav will detail his process for casting business problems as machine learning problems—from identifying which business problem to solve, to hypothesis generation, to AB testing. He’ll explain how to transform, segment, and measure variables to obtain meaningful data unique to each company, and share examples of how businesses he’s worked with have implemented these technologies to analyze specific areas of their business and resolve their toughest problems.
As Managing Director of Machine Learning, Sourav is responsible for the overall delivery of data science and data product services to make clients successful. Before Manifold, Sourav led teams to build data products across the technology stack, from smart thermostats and security cams (Google / Nest) to power grid forecasting (AutoGrid) to wireless communication chips (Qualcomm). He holds patents for his work, has been published in several IEEE journals, and has won numerous awards. He earned his Ph.D., MS, and BS degrees from MIT in Electrical Engineering and Computer Science.
Видео Using Machine Learning and Data Science to Solve Real Business Problems (DataEDGE 2018) канала Berkeley School of Information
Sourav Dey, Managing Director and Head of Data Science at Manifold, will talk about the importance for today’s companies to adopt ML and data science and how they can do it. Using specific real world use cases, Sourav will detail his process for casting business problems as machine learning problems—from identifying which business problem to solve, to hypothesis generation, to AB testing. He’ll explain how to transform, segment, and measure variables to obtain meaningful data unique to each company, and share examples of how businesses he’s worked with have implemented these technologies to analyze specific areas of their business and resolve their toughest problems.
As Managing Director of Machine Learning, Sourav is responsible for the overall delivery of data science and data product services to make clients successful. Before Manifold, Sourav led teams to build data products across the technology stack, from smart thermostats and security cams (Google / Nest) to power grid forecasting (AutoGrid) to wireless communication chips (Qualcomm). He holds patents for his work, has been published in several IEEE journals, and has won numerous awards. He earned his Ph.D., MS, and BS degrees from MIT in Electrical Engineering and Computer Science.
Видео Using Machine Learning and Data Science to Solve Real Business Problems (DataEDGE 2018) канала Berkeley School of Information
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16 июня 2018 г. 4:47:50
00:29:06
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